A PyTorch implementation of the paper https://arxiv.org/abs/1811.06861. It presents a reconstruction-based approach to anomaly detection with focus on surface defects.

ThirdEye is an integrated tool for realtime monitoring of time series and interactive root-cause analysis.

autoupdate paper list

Unsupervised Anomaly Detection System for Univariate Time Series

The project focuses on detecting anomalies in images using autoencoder neural networks. An autoencoder learns to reconstruct normal images and can classify images as anomalies when the reconstruction error exceeds a certain threshold. The code in this repository implements an autoencoder-based anomaly detection method using TensorFlow.

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection

A python library for user-friendly forecasting and anomaly detection on time series.

Resources for working with time series and sequence data

A machine learning library for detecting anomalies in signals.

Demonstration of LSDB and TAPE, prepared for the Rare Gems in Big Data 2024 meeting

A high-level machine learning and deep learning library for the PHP language.

SimAD, deep learning, anomaly detection, outlier detection, time series

PatchAD, deep learning, anomaly detection, outlier detection, time series

Evaluation Tool for Anomaly Detection Algorithms on Time Series

Python framework for automated time series classification and regression

Quadra: Effortless and reproducible deep learning workflows with configuration files.

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

A large collection of system log datasets for AI-driven log analytics [ISSRE'23]